Planning to do some deep learning course sessions e.g. fastai , google ML crash course etc. Also try to understand common tools (tensorflow, jupyter notebook, numpy, pandas, pytorch) and practices e.g. Convoluation neutral nets, SGD used to solve learning problems.

About 3 years ago I wrote some Python and Kivy code for my Samsung Galaxy S4 in QPython. Unfortunately, QPython updated and broke its kivy compatibility. I've been waiting for them to fix it, but mostly have given up. So instead, just investigate how to turn the kivy code into an .apk for installation on an Android device! There are directions for this on the kivy website.

What is kompose?

Explore the GraphQl (v4) GitHub Api and do a small project in (Elixir would be the choice)

Starting from prometheus ( and grafana if needed), learn how to monitor kubernetes and docker and do some valid alert/graph etc.

Description

Mental poker is a principle and also specific protocol to play card games without a single trusted party. This includes shuffling cards, enforcing card visibility and commitment schemes. Imagine playing rock-paper-scissors via phone only.

The usual baby-phones and phone based surveillance solutions do not fit my needs:

2018

new hack

motivation

Lots of crucial steps in the SUSE/openSUSE product build workflow are not known or not even accessible by many people but hidden as "custom scripts" on "some machine" in the worst cases. Nowadays infrastructure and build pipelines should be written as code, e.g. in git repos, with UI frontends to show the always current state of what is going on, what needs to be done to release products, where are problems. The least we can do is learn a bit more in this direction.